EP3688626A1 - Activation d'agents autonomes destinée à faire la distinction entre des questions et des demandes - Google Patents

Activation d'agents autonomes destinée à faire la distinction entre des questions et des demandes

Info

Publication number
EP3688626A1
EP3688626A1 EP18786640.5A EP18786640A EP3688626A1 EP 3688626 A1 EP3688626 A1 EP 3688626A1 EP 18786640 A EP18786640 A EP 18786640A EP 3688626 A1 EP3688626 A1 EP 3688626A1
Authority
EP
European Patent Office
Prior art keywords
utterance
classification
request
question
word
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Withdrawn
Application number
EP18786640.5A
Other languages
German (de)
English (en)
Inventor
Boris Galitsky
Vishal Vishnoi
Xin Xu
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Oracle International Corp
Original Assignee
Oracle International Corp
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Oracle International Corp filed Critical Oracle International Corp
Publication of EP3688626A1 publication Critical patent/EP3688626A1/fr
Withdrawn legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/30—Semantic analysis
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00—Speech recognition
    • G10L15/08—Speech classification or search
    • G10L15/18—Speech classification or search using natural language modelling
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/35—Clustering; Classification
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/20—Natural language analysis
    • G06F40/205—Parsing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/20—Natural language analysis
    • G06F40/253—Grammatical analysis; Style critique
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/20—Natural language analysis
    • G06F40/279—Recognition of textual entities
    • G06F40/289—Phrasal analysis, e.g. finite state techniques or chunking
    • G06F40/295—Named entity recognition

Definitions

  • the rules include responsive to determining a linguistic template match, classifying the utterance as a request.
  • the rules further include responsive to determining that the utterance includes an imperative verb as a first word of the utterance, classifying the utterance as a request.
  • the rules further include responsive to identifying one or more predefined request keywords in the utterance, classifying the utterance as a request.
  • the rules further include responsive to identifying one or more predefined question keywords in the utterance, classifying the utterance as a question.
  • the system is further configured, based on the classification, to send a message to a user device or adjust a configuration of an external device.
  • FIG. 2 depicts an example of a parse tree, in accordance with an aspect.
  • aspects disclosed herein provide technical improvements to the area of computer- implemented linguistics by providing improved classification of text. More specifically, certain aspects use linguistics to determine whether text is a question or a request for an action to be performed. As discussed above, existing solutions for autonomous agents are unable to discriminate between a question and a transactional request, leading to a failed interaction between agent and user.
  • Certain aspects use linguistic analysis via parse trees and templates in conjunction with keyword analysis. Certain keywords such as imperative verbs can indicate that the utterance is a request for action. Similarly, whether an utterance includes certain combinations of words of particular types such as mental verbs or specific prefixes can be indicative of whether the sentence is a request for an action to be performed. Certain aspects supplement linguistic processing with machine learning, for example to further improve analysis or allow for customization.
  • An utterance can include a request that is formulated explicitly (e.g., "please turn up the heat” or implicitly (e.g., "it is cold.”).
  • Transactional requests can be disguised as questions, for example, a simple question “what is my account balance” may be a transactional request to select an account and execute a database query to determine the account balance.
  • a user may request a desired state rather than an explicit action to achieve the state. For example, utterance "I am too cold” indicates not a question but a desired state that can be achieved by turning on the heater.
  • user device 170 communicates with autonomous agent 101 to facilitate user questions and requests.
  • Classification application 102 receives message 181 from user device 170.
  • Message 181 is a user utterance that reads "Transfer funds from checking to savings.”
  • classification application 102 determines a presence of a leading imperative verb "transfer” and determines that message 181 is a request.
  • Autonomous agent 102 prompts the user to "please confirm the amount” by sending message 182 to user device 170.
  • user device 170 sends a follow-on message 183 that reads "how do I check my balance?" to autonomous agent 101.
  • classification application 102 determines the user's intent, specifically, a desire for information, and sends back message 184 aiding the user in checking his balance.
  • FIG. 2 depicts an example of a parse tree, in accordance with an aspect.
  • FIG. 2 depicts parse tree 200, which parser 131 generates from the sentence "Turn on the light.”
  • Parse tree 200 includes nodes 201 -204. Each node is indicated by a type, which can in turn be further refined by additional analysis. Table 1 describes examples of types, but others are possible. Notation Description
  • matcher 132 does not categorize the utterance “tell me how to check an account balance” as a transaction due to the absence of the pronoun.
  • FIG. 6 depicts a flowchart illustrating an example of a process for training a classification model to determine informative text for indexing, in accordance with an aspect.
  • classification model 150 can be trained to discriminate between questions and requests.
  • Training data 160 can include two training sets, such as a training set with text identified as requests and a second training set with text identified as questions.
  • Training data 160 can include text and/or associated parse trees.
  • process 600 involves receiving a determined classification from the classification model.
  • server 712 may include one or more applications to analyze and consolidate data feeds and/or event updates received from users of client computing devices 802, 804, 806, and 808.
  • data feeds and/or event updates may include, but are not limited to, Twitter® feeds, Facebook® updates or real-time updates received from one or more third party information sources and continuous data streams, which may include real-time events related to sensor data applications, financial tickers, network performance measuring tools (e.g., network monitoring and traffic management applications), clickstream analysis tools, automobile traffic monitoring, and the like.
  • Server 712 may also include one or more applications to display the data feeds and/or real-time events via one or more display devices of client computing devices 702, 704, 706, and 708.
  • the cloud infrastructure system may be better available to carry out tasks on large data sets based on demand from a business, government agency, research organization, private individual, group of like-minded individuals or organizations, or other entity.
  • cloud infrastructure system 800 may include an identity management module 828.
  • Identity management module 828 may be configured to provide identity services, such as access management and authorization services in cloud infrastructure system 800.
  • identity management module 828 may control information about customers who wish to utilize the services provided by cloud infrastructure system 802. Such information can include information that authenticates the identities of such customers and information that describes which actions those customers are authorized to perform relative to various system resources (e.g., files, directories, applications, communication ports, memory segments, etc.)
  • Identity management module 828 may also include the management of descriptive information about each customer and about how and by whom that descriptive information can be accessed and modified.
  • User interface input devices may also include eye gesture recognition devices such as the Google Glass® blink detector that detects eye activity (e.g., 'blinking' while taking pictures and/or making a menu selection) from users and transforms the eye gestures as input into an input device (e.g., Google Glass®). Additionally, user interface input devices may include voice recognition sensing devices that enable users to interact with voice recognition systems (e.g., Siri® navigator), through voice commands.
  • eye gesture recognition devices such as the Google Glass® blink detector that detects eye activity (e.g., 'blinking' while taking pictures and/or making a menu selection) from users and transforms the eye gestures as input into an input device (e.g., Google Glass®).
  • user interface input devices may include voice recognition sensing devices that enable users to interact with voice recognition systems (e.g., Siri® navigator), through voice commands.
  • voice recognition systems e.g., Siri® navigator
  • Computer-readable storage media 922 containing code, or portions of code can also include any appropriate media known or used in the art, including storage media and communication media, such as but not limited to, volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage and/or transmission of information.
  • This can include tangible, non-transitory computer-readable storage media such as RAM, ROM, electronically erasable programmable ROM (EEPROM), flash memory or other memory technology, CD-ROM, digital versatile disk (DVD), or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or other tangible computer readable media.

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  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Health & Medical Sciences (AREA)
  • Artificial Intelligence (AREA)
  • Audiology, Speech & Language Pathology (AREA)
  • Computational Linguistics (AREA)
  • General Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Health & Medical Sciences (AREA)
  • Human Computer Interaction (AREA)
  • Acoustics & Sound (AREA)
  • Multimedia (AREA)
  • Data Mining & Analysis (AREA)
  • Databases & Information Systems (AREA)
  • Machine Translation (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)

Abstract

La présente invention concerne des systèmes, des dispositifs, et des procédés se rapportant à une classification de texte. Un système de classification de texte accède à un énoncé de texte. L'énoncé comprend au moins un mot. Le système de classification de texte génère un arbre d'analyse pour l'énoncé. L'arbre d'analyse comprend au moins un nœud terminal ayant un type de mot. Le nœud de terminal représente un mot de l'énoncé. Le système de classification de texte applique au moins une règle au texte. Le système de classification de texte classifie ensuite l'énoncé en tant qu'une question ou une demande destinée à un agent autonome pour réaliser une action.
EP18786640.5A 2017-09-28 2018-09-28 Activation d'agents autonomes destinée à faire la distinction entre des questions et des demandes Withdrawn EP3688626A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US201762564868P 2017-09-28 2017-09-28
PCT/US2018/053392 WO2019067878A1 (fr) 2017-09-28 2018-09-28 Activation d'agents autonomes destinée à faire la distinction entre des questions et des demandes

Publications (1)

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EP3688626A1 true EP3688626A1 (fr) 2020-08-05

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US (2) US10796099B2 (fr)
EP (1) EP3688626A1 (fr)
JP (2) JP7214719B2 (fr)
CN (2) CN111149107B (fr)
WO (1) WO2019067878A1 (fr)

Families Citing this family (21)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11373632B2 (en) 2017-05-10 2022-06-28 Oracle International Corporation Using communicative discourse trees to create a virtual persuasive dialogue
US11586827B2 (en) 2017-05-10 2023-02-21 Oracle International Corporation Generating desired discourse structure from an arbitrary text
US10599885B2 (en) 2017-05-10 2020-03-24 Oracle International Corporation Utilizing discourse structure of noisy user-generated content for chatbot learning
US11100144B2 (en) 2017-06-15 2021-08-24 Oracle International Corporation Data loss prevention system for cloud security based on document discourse analysis
US10796099B2 (en) * 2017-09-28 2020-10-06 Oracle International Corporation Enabling autonomous agents to discriminate between questions and requests
CN117114001A (zh) 2017-09-28 2023-11-24 甲骨文国际公司 基于命名实体的解析和识别确定跨文档的修辞相互关系
US10832658B2 (en) * 2017-11-15 2020-11-10 International Business Machines Corporation Quantized dialog language model for dialog systems
US11537645B2 (en) 2018-01-30 2022-12-27 Oracle International Corporation Building dialogue structure by using communicative discourse trees
WO2019217722A1 (fr) 2018-05-09 2019-11-14 Oracle International Corporation Constructions d'arbres de discours imaginaires pour améliorer la réponse à des questions convergentes
US11455494B2 (en) 2018-05-30 2022-09-27 Oracle International Corporation Automated building of expanded datasets for training of autonomous agents
US11258902B2 (en) 2018-10-02 2022-02-22 Verint Americas Inc. Partial automation of text chat conversations
US11586980B2 (en) 2019-01-18 2023-02-21 Verint Americas Inc. IVA performance dashboard and interactive model and method
US11467817B2 (en) * 2019-01-28 2022-10-11 Adobe Inc. Software component defect prediction using classification models that generate hierarchical component classifications
KR20210015234A (ko) * 2019-08-01 2021-02-10 삼성전자주식회사 전자 장치, 및 그의 음성 명령에 따른 기능이 실행되도록 제어하는 방법
US11184298B2 (en) * 2019-08-28 2021-11-23 International Business Machines Corporation Methods and systems for improving chatbot intent training by correlating user feedback provided subsequent to a failed response to an initial user intent
US11741308B2 (en) 2020-05-14 2023-08-29 Oracle International Corporation Method and system for constructing data queries from conversational input
CN112380344B (zh) * 2020-11-19 2023-08-22 平安科技（深圳）有限公司 文本分类的方法、话题生成的方法、装置、设备及介质
CN112395394B (zh) * 2020-11-27 2024-04-26 安徽迪科数金科技有限公司 短文本语义理解模板检验方法、模板生成方法及装置
US11321289B1 (en) * 2021-06-10 2022-05-03 Prime Research Solutions LLC Digital screening platform with framework accuracy questions
US20230025709A1 (en) * 2021-07-21 2023-01-26 Google Llc Transferring dialog data from an initially invoked automated assistant to a subsequently invoked automated assistant
US20230410190A1 (en) * 2022-06-17 2023-12-21 Truist Bank User interface experience with different representations of banking functions

Family Cites Families (81)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
FR2696853B1 (fr) 1992-10-12 1994-12-23 Bull Sa Procédé d'aide à l'optimisation d'une requête d'un système de gestion, de base de données relationnel et procédé d'analyse syntaxique en résultant.
JPH07160717A (ja) * 1993-12-13 1995-06-23 Matsushita Electric Ind Co Ltd 隣接発話間関係認識装置
US5715468A (en) * 1994-09-30 1998-02-03 Budzinski; Robert Lucius Memory system for storing and retrieving experience and knowledge with natural language
US8725493B2 (en) 2004-01-06 2014-05-13 Neuric Llc Natural language parsing method to provide conceptual flow
US6112168A (en) 1997-10-20 2000-08-29 Microsoft Corporation Automatically recognizing the discourse structure of a body of text
US20070294229A1 (en) 1998-05-28 2007-12-20 Q-Phrase Llc Chat conversation methods traversing a provisional scaffold of meanings
US7152031B1 (en) 2000-02-25 2006-12-19 Novell, Inc. Construction, manipulation, and comparison of a multi-dimensional semantic space
JP2001167087A (ja) 1999-12-14 2001-06-22 Fujitsu Ltd 構造化文書検索装置，構造化文書検索方法，構造化文書検索用プログラム記録媒体および構造化文書検索用インデックス作成方法
US20010053968A1 (en) 2000-01-10 2001-12-20 Iaskweb, Inc. System, method, and computer program product for responding to natural language queries
US20020046018A1 (en) 2000-05-11 2002-04-18 Daniel Marcu Discourse parsing and summarization
US6731307B1 (en) 2000-10-30 2004-05-04 Koninklije Philips Electronics N.V. User interface/entertainment device that simulates personal interaction and responds to user's mental state and/or personality
US7519529B1 (en) 2001-06-29 2009-04-14 Microsoft Corporation System and methods for inferring informational goals and preferred level of detail of results in response to questions posed to an automated information-retrieval or question-answering service
US7127208B2 (en) 2002-01-23 2006-10-24 Educational Testing Service Automated annotation
US7305336B2 (en) 2002-08-30 2007-12-04 Fuji Xerox Co., Ltd. System and method for summarization combining natural language generation with structural analysis
US8335683B2 (en) * 2003-01-23 2012-12-18 Microsoft Corporation System for using statistical classifiers for spoken language understanding
US20040148170A1 (en) 2003-01-23 2004-07-29 Alejandro Acero Statistical classifiers for spoken language understanding and command/control scenarios
US7610190B2 (en) 2003-10-15 2009-10-27 Fuji Xerox Co., Ltd. Systems and methods for hybrid text summarization
US9646107B2 (en) 2004-05-28 2017-05-09 Robert T. and Virginia T. Jenkins as Trustee of the Jenkins Family Trust Method and/or system for simplifying tree expressions such as for query reduction
US7698267B2 (en) 2004-08-27 2010-04-13 The Regents Of The University Of California Searching digital information and databases
US8700404B1 (en) 2005-08-27 2014-04-15 At&T Intellectual Property Ii, L.P. System and method for using semantic and syntactic graphs for utterance classification
US20070073533A1 (en) 2005-09-23 2007-03-29 Fuji Xerox Co., Ltd. Systems and methods for structural indexing of natural language text
US20070136284A1 (en) 2005-12-12 2007-06-14 Sbc Knowledge Ventures Lp Method for constructing and repurposing rhetorical content
JP2008165718A (ja) 2007-01-05 2008-07-17 Toyota Central R&D Labs Inc 意図判定装置、意図判定方法、及びプログラム
US7925678B2 (en) 2007-01-12 2011-04-12 Loglogic, Inc. Customized reporting and mining of event data
US8639509B2 (en) * 2007-07-27 2014-01-28 Robert Bosch Gmbh Method and system for computing or determining confidence scores for parse trees at all levels
US7840556B1 (en) 2007-07-31 2010-11-23 Hewlett-Packard Development Company, L.P. Managing performance of a database query
CN101118554A (zh) * 2007-09-14 2008-02-06 中兴通讯股份有限公司 智能交互式问答系统及其处理方法
US8306967B2 (en) 2007-10-02 2012-11-06 Loglogic, Inc. Searching for associated events in log data
US7890539B2 (en) 2007-10-10 2011-02-15 Raytheon Bbn Technologies Corp. Semantic matching using predicate-argument structure
US8463594B2 (en) 2008-03-21 2013-06-11 Sauriel Llc System and method for analyzing text using emotional intelligence factors
US9646078B2 (en) 2008-05-12 2017-05-09 Groupon, Inc. Sentiment extraction from consumer reviews for providing product recommendations
JP2010020420A (ja) 2008-07-08 2010-01-28 Omron Corp 会話文解析方法、会話文解析装置、会話文解析プログラム、および、コンピュータ読取り可能記録媒体
US20100169359A1 (en) 2008-12-30 2010-07-01 Barrett Leslie A System, Method, and Apparatus for Information Extraction of Textual Documents
JP5426292B2 (ja) 2009-09-16 2014-02-26 日本放送協会 意見分類装置およびプログラム
US8355997B2 (en) * 2009-11-13 2013-01-15 Hewlett-Packard Development Company, L.P. Method and system for developing a classification tool
US8712759B2 (en) 2009-11-13 2014-04-29 Clausal Computing Oy Specializing disambiguation of a natural language expression
JP6023593B2 (ja) 2010-02-10 2016-11-09 エムモーダル アイピー エルエルシー 質問応答システムにおける関連する証拠への計算可能なガイダンスの提供
US9449080B1 (en) 2010-05-18 2016-09-20 Guangsheng Zhang System, methods, and user interface for information searching, tagging, organization, and display
WO2012040356A1 (fr) 2010-09-24 2012-03-29 International Business Machines Corporation Fourniture de questions et de réponses à évaluation de type différée à l'aide de texte à structure limitée
US11222052B2 (en) 2011-02-22 2022-01-11 Refinitiv Us Organization Llc Machine learning-based relationship association and related discovery and
US20130046757A1 (en) 2011-08-17 2013-02-21 Microsoft Corporation Indicating relationship closeness between subsnippets of a search result
US8762132B2 (en) 2011-10-20 2014-06-24 Nec Corporation Textual entailment recognition apparatus, textual entailment recognition method, and computer-readable recording medium
US20150039295A1 (en) 2011-12-20 2015-02-05 Alona Soschen Natural language processor
JP2013190985A (ja) 2012-03-13 2013-09-26 Sakae Takeuchi 知識応答システム、方法およびコンピュータプログラム
US9336297B2 (en) 2012-08-02 2016-05-10 Paypal, Inc. Content inversion for user searches and product recommendations systems and methods
US20140122083A1 (en) 2012-10-26 2014-05-01 Duan Xiaojiang Chatbot system and method with contextual input and output messages
EP2915068A4 (fr) 2012-11-02 2016-08-03 Fido Labs Inc Procédé et système de traitement de langage naturel
CN103871286A (zh) * 2012-12-07 2014-06-18 大连联达科技有限公司 一种用于互动教学平台的互动问答系统
US10452779B2 (en) 2013-05-07 2019-10-22 Paul V. Haley System for knowledge acquisition
JP6225012B2 (ja) 2013-07-31 2017-11-01 日本電信電話株式会社 発話文生成装置とその方法とプログラム
US9317260B2 (en) 2013-08-09 2016-04-19 Vmware, Inc. Query-by-example in large-scale code repositories
US9292490B2 (en) 2013-08-16 2016-03-22 International Business Machines Corporation Unsupervised learning of deep patterns for semantic parsing
CN104598445B (zh) 2013-11-01 2019-05-10 腾讯科技（深圳）有限公司 自动问答系统和方法
US10019716B1 (en) * 2013-11-21 2018-07-10 Google Llc Method for feedback submission resolution
US20150149461A1 (en) 2013-11-24 2015-05-28 Interstack, Inc System and method for analyzing unstructured data on applications, devices or networks
US9471874B2 (en) 2013-12-07 2016-10-18 International Business Machines Corporation Mining forums for solutions to questions and scoring candidate answers
WO2015159133A1 (fr) 2014-04-18 2015-10-22 Arria Data2Text Limited Procédé et appareil de planification de document
US9934306B2 (en) * 2014-05-12 2018-04-03 Microsoft Technology Licensing, Llc Identifying query intent
US10726831B2 (en) * 2014-05-20 2020-07-28 Amazon Technologies, Inc. Context interpretation in natural language processing using previous dialog acts
JP5911911B2 (ja) 2014-05-26 2016-04-27 日本電信電話株式会社 結束性判定装置、モデル学習装置、方法、及びプログラム
US9582501B1 (en) 2014-06-16 2017-02-28 Yseop Sa Techniques for automatic generation of natural language text
WO2016007883A1 (fr) 2014-07-11 2016-01-14 Halliburton Energy Services, Inc. Outil d'évaluation pour tubages de forage concentriques
US9619513B2 (en) 2014-07-29 2017-04-11 International Business Machines Corporation Changed answer notification in a question and answer system
US20160055240A1 (en) * 2014-08-22 2016-02-25 Microsoft Corporation Orphaned utterance detection system and method
US9559993B2 (en) 2014-10-02 2017-01-31 Oracle International Corporation Virtual agent proxy in a real-time chat service
US10019437B2 (en) 2015-02-23 2018-07-10 International Business Machines Corporation Facilitating information extraction via semantic abstraction
KR20170033722A (ko) * 2015-09-17 2017-03-27 삼성전자주식회사 사용자의 발화 처리 장치 및 방법과, 음성 대화 관리 장치
GB2557532A (en) 2015-10-21 2018-06-20 Google Llc Parameter collection and automatic dialog generation in dialog systems
US20170161372A1 (en) * 2015-12-04 2017-06-08 Codeq Llc Method and system for summarizing emails and extracting tasks
WO2017112813A1 (fr) 2015-12-22 2017-06-29 Sri International Assistant personnel virtuel multilingue
US11042702B2 (en) 2016-02-04 2021-06-22 International Business Machines Corporation Solving textual logic problems using a statistical approach and natural language processing
US20170286390A1 (en) * 2016-04-04 2017-10-05 Contextors Ltd. Dynamic and automatic generation of interactive text related objects
CN106649768B (zh) 2016-12-27 2021-03-16 北京百度网讯科技有限公司 基于深度问答的问答澄清方法和装置
CN106682194B (zh) 2016-12-29 2020-05-22 北京百度网讯科技有限公司 基于深度问答的答案定位方法及装置
US10839154B2 (en) 2017-05-10 2020-11-17 Oracle International Corporation Enabling chatbots by detecting and supporting affective argumentation
US10599885B2 (en) 2017-05-10 2020-03-24 Oracle International Corporation Utilizing discourse structure of noisy user-generated content for chatbot learning
US10679011B2 (en) 2017-05-10 2020-06-09 Oracle International Corporation Enabling chatbots by detecting and supporting argumentation
US10839161B2 (en) 2017-06-15 2020-11-17 Oracle International Corporation Tree kernel learning for text classification into classes of intent
US11176325B2 (en) 2017-06-26 2021-11-16 International Business Machines Corporation Adaptive evaluation of meta-relationships in semantic graphs
US10796099B2 (en) * 2017-09-28 2020-10-06 Oracle International Corporation Enabling autonomous agents to discriminate between questions and requests
US20190163756A1 (en) 2017-11-29 2019-05-30 International Business Machines Corporation Hierarchical question answering system

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US11599724B2 (en) 2023-03-07
CN111149107A (zh) 2020-05-12
US20190095425A1 (en) 2019-03-28
JP2020537223A (ja) 2020-12-17
WO2019067878A1 (fr) 2019-04-04
JP7519476B2 (ja) 2024-07-19
CN116992859A (zh) 2023-11-03
JP2023052487A (ja) 2023-04-11
US20200372223A1 (en) 2020-11-26
US10796099B2 (en) 2020-10-06
JP7214719B2 (ja) 2023-01-30
CN111149107B (zh) 2023-08-22

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